An optimized metaproteomics protocol for a holistic taxonomic and functional characterization of microbial communities from marine particles

Genes for laminarin degradation are dispersed in the genomes of particle-associated Maribacter species

Laminarin is a cytosolic storage polysaccharide of phytoplankton and macroalgae and accounts for over 10% of the world's annually fixed carbon dioxide. Algal disruption, for example, by viral lysis releases laminarin. The soluble sugar is rapidly utilized by free-living planktonic bacteria, in which sugar transporters and the degrading enzymes are frequently encoded in polysaccharide utilization loci. The annotation of flavobacterial genomes failed to identify canonical laminarin utilization loci in several particle-associated bacteria, in particular in strains of Maribacter. In this study, we report in vivo utilization of laminarin by Maribacter forsetii accompanied by additional cell growth and proliferation. Laminarin utilization coincided with the induction of an extracellular endo-laminarinase, SusC/D outer membrane oligosaccharide transporters, and a periplasmic glycosyl hydrolase family 3 protein. An ABC transport system and sugar kinases were expressed. Endo-laminarinase activity was also observed in Maribacter sp. MAR_2009_72, Maribacter sp. Hel_I_7, and Maribacter dokdonensis MAR_2009_60. Maribacter dokdonensis MAR_2009_71 lacked the large endo-laminarinase gene in the genome and had no endo-laminarinase activity. In all genomes, genes of induced proteins were scattered across the genome rather than clustered in a laminarin utilization locus. These observations revealed that the Maribacter strains investigated in this study participate in laminarin utilization, but in contrast to many free-living bacteria, there is no co-localization of genes encoding the enzymatic machinery for laminarin utilization.

Critical steps in an environmental metaproteomics workflow

Environmental metaproteomics is a rapidly advancing field that provides insights into the structure, dynamics, and metabolic activity of microbial communities. As the field is still maturing, it lacks consistent workflows, making it challenging for non-expert researchers to navigate. This review aims to introduce the workflow of environmental metaproteomics. It outlines the standard practices for sample collection, processing, and analysis, and offers strategies to overcome the unique challenges presented by common environmental matrices such as soil, freshwater, marine environments, biofilms, sludge, and symbionts. The review also highlights the bottlenecks in data analysis that are specific to metaproteomics samples and provides suggestions for researchers to obtain high-quality datasets. It includes recent benchmarking studies and descriptions of software packages specifically built for metaproteomics analysis. The article is written without assuming the reader's familiarity with single-organism proteomic workflows, making it accessible to those new to proteomics or mass spectrometry in general. This primer for environmental metaproteomics aims to improve accessibility to this exciting technology and empower researchers to tackle challenging and ambitious research questions. While it is primarily a resource for those new to the field, it should also be useful for established researchers looking to streamline or troubleshoot their metaproteomics experiments.

Marine particle microbiomes during a spring diatom bloom contain active sulfate-reducing bacteria

Phytoplankton blooms fuel marine food webs with labile dissolved carbon and also lead to the formation of particulate organic matter composed of living and dead algal cells. These particles contribute to carbon sequestration and are sites of intense algal-bacterial interactions, providing diverse niches for microbes to thrive. We analyzed 16S and 18S ribosomal RNA gene amplicon sequences obtained from 51 time points and metaproteomes from 3 time points during a spring phytoplankton bloom in a shallow location (6-10 m depth) in the North Sea. Particulate fractions larger than 10 µm diameter were collected at near daily intervals between early March and late May in 2018. Network analysis identified two major modules representing bacteria co-occurring with diatoms and with dinoflagellates, respectively. The diatom network module included known sulfate-reducing Desulfobacterota as well as potentially sulfur-oxidizing Ectothiorhodospiraceae. Metaproteome analyses confirmed presence of key enzymes involved in dissimilatory sulfate reduction, a process known to occur in sinking particles at greater depths and in sediments. Our results indicate the presence of sufficiently anoxic niches in the particle fraction of an active phytoplankton bloom to sustain sulfate reduction, and an important role of benthic-pelagic coupling for microbiomes in shallow environments. Our findings may have implications for the understanding of algal-bacterial interactions and carbon export during blooms in shallow-water coastal areas.

Novel functional insights into the microbiome inhabiting marine plastic debris: critical considerations to counteract the challenges of thin biofilms using multi-omics and comparative metaproteomics

BACKGROUND

Microbial functioning on marine plastic surfaces has been poorly documented, especially within cold climates where temperature likely impacts microbial activity and the presence of hydrocarbonoclastic microorganisms. To date, only two studies have used metaproteomics to unravel microbial genotype-phenotype linkages in the marine 'plastisphere', and these have revealed the dominance of photosynthetic microorganisms within warm climates. Advancing the functional representation of the marine plastisphere is vital for the development of specific databases cataloging the functional diversity of the associated microorganisms and their peptide and protein sequences, to fuel biotechnological discoveries. Here, we provide a comprehensive assessment for plastisphere metaproteomics, using multi-omics and data mining on thin plastic biofilms to provide unique insights into plastisphere metabolism. Our robust experimental design assessed DNA/protein co-extraction and cell lysis strategies, proteomics workflows, and diverse protein search databases, to resolve the active plastisphere taxa and their expressed functions from an understudied cold environment.

RESULTS

For the first time, we demonstrate the predominance and activity of hydrocarbonoclastic genera (Psychrobacter, Flavobacterium, Pseudomonas) within a primarily heterotrophic plastisphere. Correspondingly, oxidative phosphorylation, the citrate cycle, and carbohydrate metabolism were the dominant pathways expressed. Quorum sensing and toxin-associated proteins of Streptomyces were indicative of inter-community interactions. Stress response proteins expressed by Psychrobacter, Planococcus, and Pseudoalteromonas and proteins mediating xenobiotics degradation in Psychrobacter and Pseudoalteromonas suggested phenotypic adaptations to the toxic chemical microenvironment of the plastisphere. Interestingly, a targeted search strategy identified plastic biodegradation enzymes, including polyamidase, hydrolase, and depolymerase, expressed by rare taxa. The expression of virulence factors and mechanisms of antimicrobial resistance suggested pathogenic genera were active, despite representing a minor component of the plastisphere community.

CONCLUSION

Our study addresses a critical gap in understanding the functioning of the marine plastisphere, contributing new insights into the function and ecology of an emerging and important microbial niche. Our comprehensive multi-omics and comparative metaproteomics experimental design enhances biological interpretations to provide new perspectives on microorganisms of potential biotechnological significance beyond biodegradation and to improve the assessment of the risks associated with microorganisms colonizing marine plastic pollution. Video Abstract.

Particle-attached bacteria act as gatekeepers in the decomposition of complex phytoplankton polysaccharides

BACKGROUND

Marine microalgae (phytoplankton) mediate almost half of the worldwide photosynthetic carbon dioxide fixation and therefore play a pivotal role in global carbon cycling, most prominently during massive phytoplankton blooms. Phytoplankton biomass consists of considerable proportions of polysaccharides, substantial parts of which are rapidly remineralized by heterotrophic bacteria. We analyzed the diversity, activity, and functional potential of such polysaccharide-degrading bacteria in different size fractions during a diverse spring phytoplankton bloom at Helgoland Roads (southern North Sea) at high temporal resolution using microscopic, physicochemical, biodiversity, metagenome, and metaproteome analyses.

RESULTS

Prominent active 0.2-3 µm free-living clades comprised Aurantivirga, "Formosa", Cd. Prosiliicoccus, NS4, NS5, Amylibacter, Planktomarina, SAR11 Ia, SAR92, and SAR86, whereas BD1-7, Stappiaceae, Nitrincolaceae, Methylophagaceae, Sulfitobacter, NS9, Polaribacter, Lentimonas, CL500-3, Algibacter, and Glaciecola dominated 3-10 µm and > 10 µm particles. Particle-attached bacteria were more diverse and exhibited more dynamic adaptive shifts over time in terms of taxonomic composition and repertoires of encoded polysaccharide-targeting enzymes. In total, 305 species-level metagenome-assembled genomes were obtained, including 152 particle-attached bacteria, 100 of which were novel for the sampling site with 76 representing new species. Compared to free-living bacteria, they featured on average larger metagenome-assembled genomes with higher proportions of polysaccharide utilization loci. The latter were predicted to target a broader spectrum of polysaccharide substrates, ranging from readily soluble, simple structured storage polysaccharides (e.g., laminarin, α-glucans) to less soluble, complex structural, or secreted polysaccharides (e.g., xylans, cellulose, pectins). In particular, the potential to target poorly soluble or complex polysaccharides was more widespread among abundant and active particle-attached bacteria.

CONCLUSIONS

Particle-attached bacteria represented only 1% of all bloom-associated bacteria, yet our data suggest that many abundant active clades played a pivotal gatekeeping role in the solubilization and subsequent degradation of numerous important classes of algal glycans. The high diversity of polysaccharide niches among the most active particle-attached clades therefore is a determining factor for the proportion of algal polysaccharides that can be rapidly remineralized during generally short-lived phytoplankton bloom events. Video Abstract.

Sediment-associated microbial community profiling: sample pre-processing through sequential membrane filtration for 16S rRNA amplicon sequencing

BACKGROUND

Sequential membrane filtration as a pre-processing step for capturing sediment-associated microorganisms could provide good quality and integrity DNA that can be preserved and kept at ambient temperatures before community profiling through culture-independent molecular techniques. However, the effects of sample pre-processing via filtration on DNA-based profiling of sediment-associated microbial community diversity and composition are poorly understood. Specifically, the influences of pre-processing on the quality and quantity of extracted DNA, high-throughput DNA sequencing reads, and detected microbial taxa need further evaluation.

RESULTS

We assessed the impact of pre-processing freshwater sediment samples by sequential membrane filtration (from 10, 5 to 0.22 μm pore size) for 16S rRNA-based community profiling of sediment-associated microorganisms. Specifically, we examined if there would be method-driven differences between non- and pre-processed sediment samples regarding the quality and quantity of extracted DNA, PCR amplicon, resulting high-throughput sequencing reads, microbial diversity, and community composition. We found no significant difference in the qualities and quantities of extracted DNA and PCR amplicons, and the read abundance after bioinformatics processing (i.e., denoising and chimeric-read filtering steps) between the two methods. Although the non- and pre-processed sediment samples had more unique than shared amplicon sequence variants (ASVs), we report that their shared ASVs accounted for 74% of both methods' absolute read abundance. More so, at the genus level, the final collection filter identified most of the genera (95% of the reads) captured from the non-processed samples, with a total of 51 false-negative (2%) and 59 false-positive genera (3%). We demonstrate that while there were differences in shared and unique taxa, both methods revealed comparable microbial diversity and community composition.

CONCLUSIONS

Our observations highlight the feasibility of pre-processing sediment samples for community analysis and the need to further assess sampling strategies to help conceptualize appropriate study designs for sediment-associated microbial community profiling.

An Innovative Protocol for Metaproteomic Analyses of Microbial Pathogens in Cystic Fibrosis Sputum

Hallmarks of cystic fibrosis (CF) are increased viscosity of mucus and impaired mucociliary clearance within the airways due to mutations of the cystic fibrosis conductance regulator gene. This facilitates the colonization of the lung by microbial pathogens and the concomitant establishment of chronic infections leading to tissue damage, reduced lung function, and decreased life expectancy. Although the interplay between key CF pathogens plays a major role during disease progression, the pathophysiology of the microbial community in CF lungs remains poorly understood. Particular challenges in the analysis of the microbial population present in CF sputum is (I) the inhomogeneous, viscous, and slimy consistence of CF sputum, and (II) the high number of human proteins masking comparably low abundant microbial proteins. To address these challenges, we used 21 CF sputum samples to develop a reliable, reproducible and widely applicable protocol for sputum processing, microbial enrichment, cell disruption, protein extraction and subsequent metaproteomic analyses. As a proof of concept, we selected three sputum samples for detailed metaproteome analyses and complemented and validated metaproteome data by 16S sequencing, metabolomic as well as microscopic analyses. Applying our protocol, the number of bacterial proteins/protein groups increased from 199-425 to 392-868 in enriched samples compared to nonenriched controls. These early microbial metaproteome data suggest that the arginine deiminase pathway and multiple proteases and peptidases identified from various bacterial genera could so far be underappreciated in their contribution to the CF pathophysiology. By providing a standardized and effective protocol for sputum processing and microbial enrichment, our study represents an important basis for future studies investigating the physiology of microbial pathogens in CF in vivo – an important prerequisite for the development of novel antimicrobial therapies to combat chronic recurrent airway infection in CF.

Distinct Human Gut Microbial Taxonomic Signatures Uncovered With Different Sample Processing and Microbial Cell Disruption Methods for Metaproteomic Analysis

The use of metaproteomics for studying the human gut microbiota can shed light on the taxonomic profile and the functional role of the microbial community. Nevertheless, methods for extracting proteins from stool samples continue to evolve, in the pursuit of optimal protocols for moistening and dispersing the stool sample and for disrupting microbial cells, which are two critical steps for ensuring good protein recovery. Here, we evaluated different stool sample processing (SSP) and microbial cell disruption methods (CDMs). The combination of a longer disintegration period of the stool sample in a tube rotator with sonication increased the overall number of identified peptides and proteins. Proteobacteria, Bacteroidetes, Planctomycetes, and Euryarchaeota identification was favored by mechanical cell disruption with glass beads. In contrast, the relative abundance of Firmicutes, Actinobacteria, and Fusobacteria was improved when sonication was performed before bead beating. Tenericutes and Apicomplexa identification was enhanced by moistening the stool samples during processing and by disrupting cells with medium-sized glass beads combined with or without sonication. Human protein identifications were affected by sonication. To test the reproducibility of these gut metaproteomic analyses, we examined samples from six healthy individuals using a protocol that had shown a good taxonomic diversity and identification of proteins from Proteobacteria and humans. We also detected proteins involved in microbial functions relevant to the host and related mostly to specific taxa, such as B12 biosynthesis and short chain fatty acid (SCFA) production carried out mainly by members in the Prevotella genus and the Firmicutes phylum, respectively. The taxonomic and functional profiles obtained with the different protocols described in this work provides the researcher with valuable information when choosing the most adequate protocol for the study of certain pathologies under suspicion of being related to a specific taxon from the gut microbiota.

Identifying Robust Microbiota Signatures and Interpretable Rules to Distinguish Cancer Subtypes

Cancer can be generally defined as a cluster of systematic diseases triggered by abnormal cell proliferation and growth. With the development of biological sciences and biotechnologies, the etiology of cancer is partially revealed, including some of the most substantial pathogenic factors [either endogenous (genetics) or exogenous (environmental)]. However, some remaining factors that contribute to the tumorigenesis but have not been analyzed and discussed in detail remain. For instance, some typical correlations between microorganisms and tumorigenesis have been reported already, but previous studies are just sporadic studies on single microorganism–cancer subtype pairs and do not explain and validate the specific contribution of microbiome on tumorigenesis. On the basis of the systematic microbiome analyses of blood and cancer-associated tissues in cancer patients/controls in public domain, we performed interpretable analyses. We identified several core regulatory microorganisms that contribute to the classification of multiple tumor subtypes and established quantitative predictive models for interpretable prediction by using multiple machine learning methods. We also compared the optimal features (microorganisms) and rules identified from microbiome profiles processed using the Kraken and the SHOGUN. Collectively, our study identified new microbiome signatures and their interpretable classification rules for cancer discrimination and carried out reliable methodological comparison for robust cancer microbiome analyses, thereby promoting the development of tumor etiology at the microbiome level.